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International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)

Xie Yi
Xie Yi
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ASME Press
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Urban water supply quantity forecasting belongs to non-linear system problem. To forecast urban water supply quantity exactly, support vector machine optimized by genetic algorithm (GA-SVM) is proposed. Genetic algorithm (GA) is used to determine training parameters of support vector machine in GA-SVM. The experimental results indicate that the proposed GA-SVM model can achieve great accuracy in urban water supply quantity forecasting.

ICACTE 2009 Session 2
Key Words
1 Introduction
2. Support Vector Regression
3. Prediction of Urban Water Supply Quantity by GA-SVM
4. Experimental Analysis for Prediction of Urban Water Supply Quantity
5. Conclusion
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